UT-JupyterLab wiki

UT-JupyterLab provides UT-employees, students and users with x-accounts with an environment that contains interactive web applications (JupyterLab notebooks).
A JupyterLab notebook integrates code and its output into a single document that combines visualizations, narrative text, mathematical equations, and other rich media.
In the platform, we provide multiple programming languages. So it is a great starting point for exploratory research, education and self-study.

The UT provides UT-jupyterLab free of charge. In exchange we want to ask the users of the environment to keep in mind that they are not the only one who wants to use the environment.
Therefore, take each other into account (fair use).

You can access the environment at: https://jupyter.utwente.nl/
From outside the UT-network a VPN-connection is required!
Use your UT-account (email adress and password).

UT-JupyterLab is not suitable for serious computational tasks. For these kind of tasks there are better alternatives.
Check out the
- Virtual Research Environment (https://vre.utwente.nl/)
- HPC Wiki (https://hpc.wiki.utwente.nl/)

FAQ

Can I disconnect and keep my code or software running?
No, when you close your browser the container will be stopped.
Also when your browser crashes or is closed for any reason the container your code is running in is stopped.
Can I run long-duration computation tasks?
You can run tasks that run for days. Each month we install security updates on the platform. All servers are restarted after that. Running tasks are terminated.
Can I run Windows applications?
No, this is not supported.
Can I run multiple instances at a time?
No, you can't. A personal Docker container is spawned for you. When you login for a second time you are connected to the same container.
Can I install additional software?
Yes, you can as long as the software runs from your home directory. You can also install your own packages with pip or conda.
Installing packages with Ubuntu apt is not possible. If you need system wide available software you can contact us(see contact section) with this request.
Install Python packages for use in the default Python kernel/notebook
The Jupyter environment contains multiple Python version. If you want to install extra packages for the default Python notebook you will have to use 'pip3.8' to install them.
If you don't use that it might be installed in a different Python version.
How can I run Matlab?
You can run Matlab by starting the “remote desktop”. Matlab is in the start menu. It will take a few seconds to start.
Can I add shared files and directory's?
You can request us to add files and directory's to the /data/public location. All users will be able to read them.
Can I share files to others?
Yes, you can share files with others. Put the data in /data/shared. This location is read/write for everyone. Keep this in mind when you put something there.
After 7 days it will be removed automatically.
Can SSH into my Jupyter environment?
No, your environment is not available with SSH. You can SSH from the environment to an other host.
Also up and downloading files from Microsoft OneDrive or Google Drive can be done from a web browser in the “Remote Desktop”.
Can I use other Python versions?
Yes, you can install other Python versions with conda in you own home directory.
If you create a virtualenv with that version of Python you can also install other Python packages.
Registering the virtualenv with Jupyter also makes it possible to use it as a notebook.
More information here:Other Python versions and in a notebook (kernel).
How long will my data be kept on the environment?
Your data will be kept for 12 months if you don't login during that time. After the 12 months without a login your profile/homedir will be removed.
Can I disconnect from the environment and reconnect?
If you choose 'File' → 'logout' your session will be terminated.
When you close your browser without logging out then your session will be kept running for 1 hour.
If you log back in from anywhere with the same account you will be connected to the same session within that hour.
After this hour your session will be terminated.
Can I run OpenFOAM?
Yes, you will have to execute this module command in a terminal before you can use it: “module load openfoam/v2206”.
Can I use nbgitpuller?
Yes, you can use nbgitpuller.
With the nbgitpuller you can create a link that will open a git repository on Jupyter automatically.
How to use it is described Using nbgitpuller to share Git repositories.
Can I grade many assignments automatically?
Yes, you can read more about it Using Jupyter Notebooks with Otter to create and automatically grade assignments

Support or questions/feedback

You can contact us by e-mail: jupyter-lisa@utwente.nl
for:
- Support
- Questions/Feedback. These gives us input to see if we are on the right track and to determine what we need to change to improve the platform.

Hardware

The UT-JupyterLab cluster currently consists of:

2x:

  • Dell PowerEdge R740
  • 48 Cores / 96 Threads / Max. 2.20 GHz
  • 256 GB Memory
  • 2 x Nvidia Tesla T4 (CUDA capable for GPU-calculations)
  • 10 Gb connections for network and storage

2x:

  • Dell PowerEdge R750
  • 56 Cores / 128 Threads / Max. 2.0 GHz
  • 256 GB Memory
  • 2 x Nvidia A10 (CUDA capable for GPU-calculations)
  • 10 Gb connections for network and storage

2x: (in collaboration with the EEMCS faculty)

  • Dell PowerEdge R750
  • 72 Cores / 144 Threads / Max. 2.1 GHz
  • 256 GB Memory
  • 2 x Nvidia A16 (CUDA capable for GPU-calculations)
  • 10 Gb connections for network and storage

8x: (in collaboration with the EEMCS-DMB researchgroup)

  • Dell PowerEdge R7515
  • 64 Cores / 128 Threads / Max. 3.675 GHz
  • 1 TB Memory
  • available annually in the cluster from March to October

All data is stored on certified storage in the UT-datacenters.